Search: “tools”

OrbiSim: World Models as Differentiable Physics Engines for Embodied Intelligence

arXiv:2605.16395v1 Announce Type: cross Abstract: We present OrbiSim, a novel robotic simulation paradigm that redefines world models as a fully differentiable physics engine for embodied intelligence

safetyarxiv-cs-lg

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Overeager Coding Agents: Measuring Out-of-Scope Actions on Benign Tasks

DGX agent

arXiv:2605.18583v1 Announce Type: cross Abstract: Coding agents now run autonomously with shell, file, and network privileges. When a user issues a benign request, the agent sometimes does more than a

model-releasesarxiv-cs-ai

19 May 2026

Parameterized 4-Qubit EWL Quantum Game Circuits with Dirac-Solow-Swan Hamiltonian Integration for Quadruple Helix Disruptive Innovation Recommender Systems

arXiv:2605.18080v1 Announce Type: cross Abstract: We present a novel parameterized 4-qubit Eisert-Wilkens-Lewenstein (EWL) quantum game circuit for recommender systems in quadruple helix innovation ec

safetyarxiv-cs-ai

PULSE: Agentic Investigation with Passive Sensing for Proactive Intervention in Cancer Survivorship

arXiv:2605.17679v1 Announce Type: cross Abstract: Cancer survivors face elevated rates of depression, anxiety, and general emotional distress, yet the precise moments they most need support are often

R2V Agent: Teaching SLMs When to Ask for Help

arXiv:2605.16604v1 Announce Type: new Abstract: Efficient agentic systems should incur expensive frontier-model costs only on decisions where a cheaper local model is likely to fail. Existing LLM casc

local-aiarxiv-cs-lg

RAGA: Reading-And-Graph-building-Agent for Autonomous Knowledge Graph Construction and Retrieval-Augmented Generation

arXiv:2605.17072v1 Announce Type: new Abstract: Existing LLM-driven knowledge graph (KG) construction methods predominantly employ stateless batch processing pipelines, exhibiting structural deficienc

Red-Bandit: Test-Time Adaptation for LLM Red-Teaming via Bandit-Guided LoRA Experts

arXiv:2510.07239v2 Announce Type: replace Abstract: Automated red-teaming has emerged as a scalable approach for auditing Large Language Models (LLMs) prior to deployment, yet existing approaches lack

Tutorials

Rover: Context-aware Conflict Resolution with LLM

arXiv:2605.17279v1 Announce Type: cross Abstract: Code merging is a significant challenge, particularly in large-scale projects. Existing solutions, including program analysis and machine learning, sh

tutorialsarxiv-cs-ai

Same Signal, Different Semantics: A Cross-Framework Behavioral Analysis of Software Engineering Agents

arXiv:2605.18332v1 Announce Type: cross Abstract: Behavioral studies of LLM-based software engineering agents extract operational rules about which trajectory shapes correlate with higher resolution r

Scalable Knowledge Editing for Mixture-of-Experts LLMs via Tensor-Structured Updates

arXiv:2605.16686v1 Announce Type: new Abstract: Knowledge editing (KE) provides a lightweight alternative to repeated fine-tuning of LLMs. However, most existing KE methods target dense feed-forward l

Scale Determines Whether Language Models Organize Representation Geometry for Prediction

arXiv:2605.17084v1 Announce Type: cross Abstract: In language models, what a representation encodes is determined by the geometry of its representation space: distances, not activations, carry meaning

safetyarxiv-cs-cl

SCICONVBENCH: Benchmarking LLMs on Multi-Turn Clarification for Task Formulation in Computational Science

arXiv:2605.18630v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly deployed as scientific AI as- sistants, and a growing body of benchmarks evaluates their capabilities acro

Self-Improving CAD Generation Agents with Finite Element Analysis as Feedback

arXiv:2605.17448v1 Announce Type: cross Abstract: Computer-aided design (CAD) is the backbone of modern industrial design, yet learned CAD generators still fall short of real engineering pipelines: th

SkillJect: Effectively Automating Skill-Based Prompt Injection for Skill-Enabled Agents

arXiv:2602.14211v2 Announce Type: replace-cross Abstract: Agent skills are increasingly used to extend LLM agents with task-specific instructions, executable scripts, and auxiliary resources. While im

Some[Body] Must Receive That Pain for Agent Accountability

arXiv:2605.16872v1 Announce Type: cross Abstract: AI agents increasingly act consequentially in the real world. This creates a problem we call consequence reception: harm occurs, the producing system

Tutorials

Sparse Autoencoders are Topic Models

arXiv:2511.16309v2 Announce Type: replace Abstract: Sparse autoencoders (SAEs) are used to analyze embeddings, but their role and practical value are debated. We propose a new perspective on SAEs by d

tutorialsarxiv-cs-cv

Spatiotemporal Robustness of Temporal Logic Tasks using Multi-Objective Reasoning

arXiv:2603.29868v2 Announce Type: replace Abstract: The reliability of autonomous systems depends on their robustness, i.e., their ability to meet their objectives under uncertainty. In this paper, we

STRIDE-AI: A Threat Modeling Framework for Generative AI Security Assessment

arXiv:2605.17163v1 Announce Type: cross Abstract: Traditional cybersecurity methodologies target deterministic systems and fail to address the probabilistic nature of AI, leaving systems vulnerable to

SWoMo: Neuro-Symbolic World Model for Cataract Surgery Simulation

arXiv:2605.16530v1 Announce Type: new Abstract: Realistic surgical simulation plays a crucial role in training novice surgeons and in the development of autonomous agents. World models can scale such

agentsarxiv-cs-cv

TeleCom-Bench: How Far Are Large Language Models from Industrial Telecommunication Applications?

arXiv:2605.18025v1 Announce Type: new Abstract: While Large Language Models have achieved remarkable integration in various vertical scenarios, their deployment in the telecommunications domain remain

The Impact of AI Search on the Online Content Ecosystem: Evidence from Google and Reddit

arXiv:2605.16428v1 Announce Type: cross Abstract: Search engines traditionally complement online content platforms by directing users seeking information to external websites. The emergence of generat

safetyarxiv-cs-ai

Tutorials

The Learnability Gap in Medical Latent Diffusion

arXiv:2605.17087v1 Announce Type: new Abstract: Generative data augmentation with latent diffusion models is a promising strategy for addressing class imbalance in medical imaging, yet current approac

tutorialsarxiv-cs-cv

The Normal Distributions Indistinguishability Spectrum and its Application to Privacy-Preserving Machine Learning

arXiv:2309.01243v4 Announce Type: replace-cross Abstract: We investigate the privacy of {em any} algorithm whose outputs have Gaussian distribution. This work is motivated by the prevalence of such al

The Recovery Mechanism: Technology, Education, and What Happens When the Pattern Breaks

arXiv:2605.16283v1 Announce Type: cross Abstract: For centuries, each new technology has automated some layer of cognitive work and been absorbed by education retreating upward to teach the skills mac

Thinking with Patterns: Breaking the Perceptual Bottleneck in Visual Planning via Pattern Induction

arXiv:2605.16848v1 Announce Type: cross Abstract: Planning from raw visual input remains a significant challenge for current Vision-Language Models (VLMs), when the complexity of input is beyond their

local-aiarxiv-cs-ai

Understanding In-Context Learning on Structured Manifolds: Bridging Attention to Kernel Methods

arXiv:2506.10959v3 Announce Type: replace-cross Abstract: While in-context learning (ICL) has achieved remarkable success in natural language and vision domains, its theoretical understanding-particul

researcharxiv-cs-ai

Unveiling Memorization-Generalization Coexistence: A Case Study on Arithmetic Tasks with Label Noise

arXiv:2605.18022v1 Announce Type: cross Abstract: Highly over-parameterized models can simultaneously memorize noisy labels and generalize well, yet how these behaviors coexist remains poorly understo

Usenix'23 Extended Version: Smart Learning to Find Dumb Contracts

arXiv:2304.10726v3 Announce Type: replace-cross Abstract: We introduce the Deep Learning Vulnerability Analyzer (DLVA) for Ethereum smart contracts based on neural networks. We train DLVA to judge byt

Hardware

VeriCache: Turning Lossy KV Cache into Lossless LLM Inference

arXiv:2605.17613v1 Announce Type: cross Abstract: The large size of the KV cache has become a major bottleneck for serving LLMs with increasing context lengths. In response, many KV cache compression

hardwarearxiv-cs-lg

Vidya: An AI-Driven Modular Pipeline for Archival Automation and Semantic Metadata Enrichment

arXiv:2605.16338v1 Announce Type: cross Abstract: The large-scale digitization of historical archives has created a paradox: 'dark data'-digital objects lacking metadata for retrieval. Manual archival

researcharxiv-cs-cl

Vision-OPD: Learning to See Fine Details for Multimodal LLMs via On-Policy Self-Distillation

arXiv:2605.18740v1 Announce Type: cross Abstract: Multimodal Large Language Models (MLLMs) still struggle with fine-grained visual understanding, where answers often depend on small but decisive evide

local-aiarxiv-cs-ai

What Does the AI Doctor Value? Auditing Pluralism in the Clinical Ethics of Language Models

arXiv:2605.18738v1 Announce Type: new Abstract: Medicine is inherently pluralistic. Principles such as autonomy, beneficence, nonmaleficence, and justice routinely conflict, and such ethical dilemmas

When Is Rank-1 Steering Cheap? Geometry, Granularity, and Budgeted Search

arXiv:2605.16362v1 Announce Type: cross Abstract: Activation steering offers a lightweight way to control LLMs without retraining, but its effectiveness varies sharply across concepts. Prior work ofte

safetyarxiv-cs-ai

A Statistical Analysis for Per-Instance Evaluation of Stochastic Optimizers: Avoiding Unreliable Conclusions

arXiv:2503.16589v2 Announce Type: replace Abstract: A key trait of stochastic optimizers is that multiple runs of the same optimizer in attempting to solve the same problem can produce different resul

researcharxiv-cs-lg

A Unified Perturbation Framework for Analyzing Leaderboard Stability and Manipulation

arXiv:2605.15761v1 Announce Type: new Abstract: Evaluation leaderboards such as LMArena play a central role in benchmarking large language models by aggregating pairwise human preferences into model r

researcharxiv-cs-lg

Access Timing as Scaffolding: A Reinforcement Learning Approach to GenAI in Education

arXiv:2605.15850v1 Announce Type: cross Abstract: In recent years, generative AI (GenAI) in educational settings has become ubiquitous in students' daily lives, despite its potential to induce over-re

Adapting Foundation Vision-Language Models to Medical Diagnosis via Query-Driven Expert Bridging

model-releasesarxiv-cs-cv

arXiv:2505.21698v3 Announce Type: replace Abstract: Vision-language foundation models achieve promising performance in natural image classification, yet their direct application to medical imaging is

AgentStop: Terminating Local AI Agents Early to Save Energy in Consumer Devices

arXiv:2605.15206v1 Announce Type: cross Abstract: Autonomous agents powered by large language models (LLMs) are increasingly used to automate complex, multi-step tasks such as coding or web-based ques

local-aiarxiv-cs-ai

Can Large Language Models Imitate Human Speech for Clinical Assessment? LLM-Driven Data Augmentation for Cognitive Score Prediction

arXiv:2605.16077v1 Announce Type: new Abstract: Accurate assessment of cognitive decline from spontaneous speech remains challenging due to limited dataset size and class imbalance. In this work, we p

Can Vision Language Models Be Adaptive in Mathematics Education? A Learner Model-based Rubric Study

arXiv:2605.16011v1 Announce Type: cross Abstract: Adaptive learning refers to educational technologies that track learners' learning progress and adapt the instructional process based on individual le

Defining Cultural Capabilities for AI Evaluation: A Taxonomy Grounded in Intercultural Communication Theory

arXiv:2605.15990v1 Announce Type: new Abstract: Tremendous efforts have been put into evaluating the inclusivity and effectiveness of AI systems across cultures. However, the cultural capabilities con

applicationsarxiv-cs-cl

DexJoCo: A Benchmark and Toolkit for Task-Oriented Dexterous Manipulation on MuJoCo

model-releasesarxiv-cs-ro

arXiv:2605.16257v1 Announce Type: new Abstract: Achieving human-level manipulation requires dexterous robotic hands capable of complex object interactions. Advancing such capabilities further demands

Dynamic Plasma Shape Control with Arbitrary Sensor Subsets

arXiv:2605.15935v1 Announce Type: new Abstract: Plasma shape control in tokamaks requires a real-time controller that tracks dynamically changing shape targets while tolerating diagnostic failures. Cl

safetyarxiv-cs-ro

EndoGSim: Physics-Aware 4D Dynamic Endoscopic Scene Simulations via MLLM-Guided Gaussian Splatting

arXiv:2605.16022v1 Announce Type: new Abstract: In robot-assisted minimally invasive surgery, high-fidelity dynamic endoscopic scene reconstruction and simulation are crucial to enhancing downstream t

researcharxiv-cs-cv

Eskwai for Students: Generative AI Assistant for Legal Education in Ghana

arXiv:2605.15380v1 Announce Type: new Abstract: Recent advances in generative AI have shown their potential to be leveraged for legal education. Yet, work on the development and deployment of such sys

safetyarxiv-cs-cl

FINESSE-Bench: A Hierarchical Benchmark Suite for Financial Domain Knowledge and Technical Analysis in Large Language Models

arXiv:2605.15482v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly being applied to financial analysis, reporting, investment decision support, risk management, compliance,

From Layers to Networks: Comparing Neural Representations via Diffusion Geometry

arXiv:2605.15901v1 Announce Type: new Abstract: Diffusion geometry is a manifold learning framework that uses random walks defined by Markov transition matrices to characterize the geometry of a datas

Frontier Large Language Models Rival State-of-the-Art Planners

arXiv:2511.09378v2 Announce Type: replace Abstract: A series of influential studies established that large language models cannot reliably solve even simple planning tasks. We show that the latest gen